The company was particularly bemused by Ellison's claims that Redshift wasn't elastic. "Now I know it's called Amazon Elastic Cloud, it's just not elastic," Ellison told the keynote audience. "In other words, Amazon's database, Redshift, cannot automatically increase the number of processors to run a bigger workload, then free up those processors. Just can't do it," he said. He went on to claim you have to shut the system down, then start a new instance, copy the database to the new storage, then run it, then copy it back to the old one.

To which an Amazon spokesperson replied: Rubbish (in so many words).

"Yeah, that's factually incorrect. With Amazon Redshift, customers can resize their clusters whenever they want, or can scale compute separately from storage by using Redshift Spectrum against their data in Amazon Simple Storage Service and pay per query for just the queries they run," the spokesperson told TechCrunch.

They went on to berate Ellison, saying, "But,‎ most people know already that this sounds like Larry being Larry. No facts, wild claims, and lots of bluster."

The term elastic here is referring to the ability to scale up or down depending on the resources required for a particular job; in Ellison's example, to run a database query.

Elasticity is one of the primary advantages of cloud computing. You can dial up more resources when you require it, and if you don't need them anymore, you can dial back down. When you own your own data center, this isn't possible. Companies often buy more capacity than they need, to avoid not having enough, which means they've put out a big capital expense for capacity they might not use for some time.

If IT needed some extra resources for a big day like, say, the Black Friday holiday shopping push, they would be out of luck. IT wasn't buying a bunch of extra servers for a one-day event. That's where the cloud shines. When you require extra resources for a short-term need, you can allocate them, then shut them down when the push is over.